Systems and methods for making time-sequential measurements of biopotentials sensed in myocardial tissue

ABSTRACT

Analog or digital systems and methods generate a composite signal derived from a biological event in a time-sequential fashion. The systems and methods input a first set of signals derived from a biological event using a first group of sensors during a first time interval. The systems and methods input a second set of signals derived from the biological event during a second time interval sequentially after the first time interval using a second group of sensors. The second group of sensors has at least one common sensor that is part of the first group and other sensors that are not part of the first group. The systems and methods time align the first and second sets of signals using the signals sensed by the at least one common sensor, thereby generating the composite signal. The systems and methods time align by shifting the first and second sets of signals either with or without computing a time difference between them.

This is a continuation of application Ser. No. 08/390,540 filed on Feb.17. 1995, now abandoned.

FIELD OF THE INVENTION

The invention relates to systems and methods for acquiring, measuring,and analyzing signals derived from biological events.

BACKGROUND OF THE INVENTION

Normal sinus rhythm of the heart begins with the sinoatrial node (or "SAnode") generating a depolarization wave front. The impulse causesadjacent myocardial tissue cells in the atria to depolarize, which inturn causes adjacent myocardial tissue cells to depolarize. Thedepolarization propagates across the atria, causing the atria tocontract and empty blood from the atria into the ventricles. The impulseis next delivered via the atrioventricular node (or "AV node") and thebundle of HIS (or "HIS bundle") to myocardial tissue cells of theventricles. The depolarization of these cells propagates across theventricles, causing the ventricles to contract.

This conduction system results in the described, organized sequence ofmyocardial contraction leading to a normal heartbeat.

Sometimes aberrant conductive pathways develop in heart tissue, whichdisrupt the normal path of depolarization events. For example,anatomical obstacles in the atria or ventricles can disrupt the normalpropagation of electrical impulses. These anatomical obstacles (called"conduction blocks") can cause the electrical impulse to degenerate intoseveral circular wavelets that circulate about the obstacles. Thesewavelets, called "reentry circuits," disrupt the normal activation ofthe atria or ventricles. As a further example, localized regions ofischemic myocardial tissue may propagate depolarization events slowerthan normal myocardial tissue. The ischemic region, also called a "slowconduction zone," creates errant, circular propagation patterns, called"circus motion." The circus motion also disrupts the normaldepolarization patterns, thereby disrupting the normal contraction ofheart tissue.

The aberrant conductive pathways create abnormal, irregular, andsometimes life-threatening heart rhythms, called arrhythmias. Anarrhythmia can take place in the atria, for example, as in atrialtachycardia (AT) or atrial flutter (AF). The arrhythmia can also takeplace in the ventricle, for example, as in ventricular tachycardia (VT).

In treating arrhythmias, it is essential that the location of thesources of the aberrant pathways (call foci) be located. Once located,the tissue in the foci can be destroyed, or ablated, by heat, chemicals,or other means. Ablation can remove the aberrant conductive pathway,restoring normal myocardial contraction.

Today, physicians examine the propagation of electrical impulses inheart tissue to locate aberrant conductive pathways. The techniques usedto analyze these pathways, commonly called "mapping," identify regionsin the heart tissue, called foci, which can be ablated to treat thearrhythmia.

One form of conventional cardiac tissue mapping techniques uses multipleelectrodes positioned in contact with epicardial heart tissue to obtainmultiple electrograms. The physician stimulates myocardial tissue byintroducing pacing signals and visually observes the morphologies of theelectrograms recorded during pacing, which this Specification will referto as "paced electrograms." The physician visually compares the patternsof paced electrograms to those previously recorded during an arrhythmiaepisode to locate tissue regions appropriate for ablation. Theseconventional mapping techniques require invasive open heart surgicaltechniques to position the electrodes on the epicardial surface of theheart.

Conventional epicardial electrogram processing techniques used fordetecting local electrical events in heart tissue are often unable tointerpret electrograms with multiple morphologies. Such electrograms areencountered, for example, when mapping a heart undergoing ventriculartachycardia (VT). For this and other reasons, consistently high correctfoci identification rates (CIR) cannot be achieved with currentmulti-electrode mapping technologies.

Another form of conventional cardiac tissue mapping technique, calledpace mapping, uses a roving electrode in a heart chamber for pacing theheart at various endocardial locations. In searching for the VT foci,the physician must visually compare all paced electrocardiograms(recorded by twelve lead body surface electrocardiograms (ECG's)) tothose previously recorded during an induced VT. The physician mustconstantly relocate the roving electrode to a new location tosystematically map the endocardium.

These techniques are complicated and time consuming. They requirerepeated manipulation and movement of the pacing electrodes. At the sametime, they require the physician to visually assimilate and interpretthe electrocardiograms.

Furthermore, artifacts caused by the pacing signals can distort theelectrocardiograms. The pacing artifacts can mask the beginning of theQ-wave in the electrocardiogram. In body surface mapping, the morphologyof the pacing artifact visually differs from the morphology of theelectrocardiogram. A trained physician is therefore able to visuallydifferentiate between a pacing artifact and the electrocardiogrammorphology. This is not always the case in endocardial or epicardialmapping, in which there can be a very close similarity between themorphology of the pacing artifact and the bipolar electrogrammorphology. Under the best conditions, the pacing artifact andelectrogram complex are separated in time, and therefore can bedistinguished from one another by a trained physician. Under otherconditions, however, the presence of the pacing artifact can sometimesmask the entire bipolar electrogram. In addition, its likeness to thebipolar electrogram often makes it difficult or impossible for even atrained physician to detect the beginning of depolarization withaccuracy.

There thus remains a real need for cardiac mapping and ablation systemsand procedures that simplify the analysis of electrograms and the use ofelectrograms to locate appropriate arrhythmogenic foci.

SUMMARY OF THE INVENTION

A principal objective of the invention is to provide improved systemsand methods to examine biological events quickly and accurately.

One aspect of the invention provides systems and methods for generatinga composite signal derived from biopotentials sensed in myocardialtissue. The systems and methods input a first set of signals, whichcomprises a plurality of biopotentials sensed in myocardial tissue usinga first group of the sensors during a first time interval. The systemsand methods input a second set of signals, which comprises a pluralityof bipotentials sensed in myocardial tissue during a second timeinterval sequentially after the first time interval using a second groupof the sensors. The second group of sensors has at least one commonsensor that is part of the first group and other sensors That are notpart of the first group. At least one of the biopotentials in the firstset of signals is sensed in the first time interval and not in thesecond time interval, and at least one of the biopotentials in thesecond set of signals is sensed in the second time interval and not inthe first time interval. The systems and methods time align the firstand second sets of signals using biopotentials sensed in myocardialtissue by the at least one common sensor, thereby generating thecomposite signal arranged for analysis as if all biopotentials weresensed during a common Time interval. The composite signal provides adiagnostic indicator.

In one preferred embodiment, the systems and methods time align byshifting the first and second sets of signals without computing a timedifference between them. In this embodiment, the systems and methodsshift the first and second sets of signals based upon the locations ofmaximal slopes of the signals coming from the common sensor.

In another preferred embodiment, the systems and methods time align byshifting the first and second sets of signals by computing a timedifference between the first and second sets of signals for the purposeof time-registering them. In this embodiment, the systems and methodscompute the time difference based upon the time differences of peaks ofthe signals coming from the common sensor.

Another aspect of the invention provides systems and methods that employfirst and second processing channels for processing biopotentials sensedby first, second, and third signal sensors in myocardial tissue. Thesystems and methods couple The first and second signal sensors to thefirst and second processing channels during a first time interval Torecord a first set of signals comprising a plurality of biopotentialssensed in myocardial tissue. The systems and methods couple the firstand third signal sensors to the first and second processing channelsduring a second time interval different than the first time interval torecord a second set of signals comprising a plurality of biopotentialssensed in myocardial tissue. At least one of the biopotentials in thefirst set of signals is sensed in the first time interval and not in thesecond time interval, and at least one of the biopotentials in thesecond set of signals is sensed in the second time interval and not inthe first time interval. The systems and methods time align the firstand second sets of signals by using biopotentials sensed by the firstsignal sensor to create a composite set of signals comprising thebiopotentials sensed by the first, second, and third sensors arrangedfor analysis as if all biopotentials were recorded during a common timeinterval. The composite set provides a diagnostic indicator.

In a preferred embodiment, the systems and methods time align byshifting the first and second sets of signals without computing a timedifference between them. In this embodiment, the systems and methodsshift the first and second sets of signals based upon the locations ofmaximal slopes of the signals coming from the first signal sensor.

In another preferred embodiment, the systems and methods time align byshifting the first and second sets of signals by computing a timedifference between the first and second sets of signals for the purposeof time-registering them. In this embodiment, the systems and methodscompute the time difference based upon the time differences of peaks ofthe signals coming from the first signal sensor.

Either aspect of the invention is applicable for processing diversetypes of derived biological signals, such as respiratory signals,electrograms, electrocardiograms, tissue biopotentials, pressure waves,electrogastrograms, electromyograms, electroencephalograms, impedancemeasurements, and temperature measurements.

Other features and advantages of the inventions are set forth in thefollowing Description and Drawings, as well as in the appended Claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a diagrammatic view of a system, which embodies the featuresof the invention, for accessing a targeted tissue region in the body fordiagnostic or therapeutic purposes;

FIG. 1B is a diagrammatic view of the system shown in FIG. 1A, with theinclusion of a roving pacing probe and additional features to aid thephysician in conducting diagnosis and therapeutic techniques accordingto the invention;

FIG. 2 is an enlarged perspective view of a multiple-electrode structureused in association with the system shown in FIG. 1;

FIG. 3 is an enlarged view of an ablation probe usable in associationwith the system shown in FIGS. 1A and 1B;

FIG. 4A is a diagrammatic view of the process controller shown in FIGS.1A and 1B, which locates by electrogram matching a site appropriate forablation;

FIG. 4B is a schematic view of a slow conduction zone in myocardialtissue and the circular propagation patterns (called circus motion) itcreates;

FIG. 5 is a flow chart showing a pattern matching technique that theprocess controller shown in FIG. 4A can employ for matching electrogramsaccording to the invention;

FIGS. 6A to 6E are representative electrogram morphologies processed inaccordance with the pattern matching technique shown in FIG. 5;

FIGS. 7A and 7B are, respectively, a flow chart and illustrative waveshape showing a symmetry matching technique that the process controllershown in FIG. 4A can employ for matching electrograms according to theinvention;

FIGS. 8A to 8C are representative electrogram morphologies processed inaccordance with the symmetry matching technique shown in FIG. 7A;

FIG. 9 is a flow chart showing a matched filtering technique that theprocess controller shown in FIG. 4A can employ for matching electrogramsaccording to the invention;

FIG. 10 is a flow chart showing a cross correlation coefficienttechnique that the process controller shown in FIG. 4A can employ formatching electrograms according to the invention;

FIGS. 11A and 11B are representative electrogram morphologies processedin accordance with the cross correlation coefficient technique shown inFIG. 10;

FIG. 12 is a flow chart showing a norm of the difference technique thatthe process controller shown in FIG. 4A can employ for matchingelectrograms according to the invention;

FIGS. 13A and 13B are representative electrogram morphologies processedin accordance with the norm of the difference technique shown in FIG.12;

FIG. 14A is a flow chart showing a filtering technique that the processcontroller shown in FIG. 4A can employ for removing pacing artifactsaccording to the invention;

FIG. 14B is a diagram showing the implementation of the filteringtechnique shown in FIG. 14A as a median filter;

FIG. 14C is a diagram showing the implementation of the filteringtechnique shown in FIG. 14A as a non-median filter;

FIG. 15A to D; 16A to D; 17A to D are representative electrogrammorphologies showing the effect of the sort position selection criteriain removing the pacing artifact employing the technique shown in FIG.14;

FIGS. 18A to C are representative electrogram morphologies showing theeffect of the sample window size in removing the pacing artifactemploying the technique shown in FIG. 14;

FIG. 19 is a diagrammatic view of an adaptive filtering technique thatthe process controller shown in FIG. 4A can employ for removing pacingartifacts according to the invention;

FIGS. 20A and 20B are representative electrogram morphologies processedby the adaptive filtering technique shown in FIG. 19 to remove a pacingartifact;

FIG. 21 is a diagrammatic flow chart showing the operation of thetime-sequential mode of the process controller shown in FIG. 1 increating an electrogram composite over different time intervals;

FIGS. 22A to 22D show representative individual electrograms taken atdifferent time intervals during the time-sequential mode shown in FIG.21, before time-alignment;

FIGS. 23A to 23D show the representative individual electrograms shownin FIGS. 22A to 22D, after time-alignment, to form the electrogramcomposite;

FIG. 24 shows a pace electrogram with three pacing artifacts, beforeadaptive filtering;

FIGS. 25A to C show the artifact signals of the three pacing artifactsshown in FIG. 24, manually selected by the physician, before alignmentand truncation;

FIGS. 26A to C show the artifact signals of the three pacing artifactsshown in FIG. 25A to C, after alignment and truncation;

FIG. 27 shows the artifact template that results from averaging thethree artifact signals shown in FIGS. 26A to C; and

FIGS. 28A and B show the alignment of the first pacing artifact (in FIG.28A) with the artifact template (in FIG. 28B).

The invention may be embodied in several forms without departing fromits spirit or essential characteristics. The scope of the invention isdefined in the appended claims, rather than in the specific descriptionpreceding them. All embodiments that fall within the meaning and rangeof equivalency of the claims are therefore intended to be embraced bythe claims.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1A shows the components of a system 10 for analyzing body tissuebiopotential morphologies for diagnostic or therapeutic purposes. Theillustrated embodiment shows the system 10 being used to examine thedepolarization of heart tissue that is subject to an arrhythmia. In thisembodiment, the system 10 serves to locate an arrhythmogenic focus forremoval by ablation. The invention is well suited for use in conductingelectrical therapy of the heart.

Still, it should be appreciated that the invention is applicable for usein other regions of the body where tissue biopotential morphologies canbe ascertained by analyzing electrical events in the tissue. Forexample, the various aspects of the invention have application inprocedures for analyzing brain or neurologic tissue.

FIG. 1A shows the system 10 analyzing endocardial electrical events,using catheter-based, vascular access techniques. Still, many aspects ofthe invention can be used in association with techniques that do notrequire any intrusion into the body, like surface electrocardiograms orelectroencephalograms. Many of the aspects of the invention also can beused with invasive surgical techniques, like in open chest or open heartsurgery, or during brain surgery.

In particular, FIG. 1A shows the system 10 analyzing electrical eventswithin a selected region 12 inside a human heart. FIGS. 1A and 1Bgenerally show the system 10 deployed in the left ventricle of theheart. Of course, the system 10 can be deployed in other regions of theheart, too. It should also be noted that the heart shown in the FIG. 1is not anatomically accurate. FIGS. 1A and 1B show the heart indiagrammatic form to demonstrate the features of the invention.

The system 10 includes a mapping probe 14 and an ablation probe 16. InFIG. 1A, each is separately introduced into the selected heart region 12through a vein or artery (typically the femoral vein or artery) throughsuitable percutaneous access. Alternatively, the mapping probe 14 andablation probe 16 can be assembled in an integrated structure forsimultaneous introduction and deployment in the heart region 12.

Further details of the deployment and structures of the probes 14 and 16are set forth in pending U.S. patent application Ser. No. 08/033,641,filed Mar. 16, 1993, now U.S. Pat. No. 5,636,634 entitled "Systems andMethods Using Guide Sheaths for Introducing, Deploying, and StabilizingCardiac Mapping and Ablation Probes."

The mapping probe 14 has a flexible catheter body 18. The distal end ofthe catheter body 18 carries a three dimensional multiple-electrodestructure 20. In the illustrated embodiment, the structure 20 takes theform of a basket defining an open interior space 22 (see FIG. 2). Itshould be appreciated that other three dimensional structures could beused.

As FIG. 2 shows, the illustrated basket structure 20 comprises a basemember 26 and an end cap 28. Generally flexible splines 30 extend in acircumferentially spaced relationship between the base member 26 and theend cap 28.

The splines 30 are preferably made of a resilient, biologically inertmaterial, like Nitinol metal or silicone rubber. The splines 30 areconnected between the base member 26 and the end cap 28 in a resilient,pretensed, radially expanded condition, to bend and conform to theendocardial tissue surface they contact. In the illustrated embodiment(see FIG. 2), eight splines 30 form the basket structure 20. Additionalor fewer splines 30 could be used.

The splines 30 carry an array of electrodes 24. In the illustratedembodiment, each spline 30 carries eight electrodes 24. Of course,additional or fewer electrodes 24 can be used.

A slidable sheath 19 is movable along the axis of the catheter body 18(shown by arrows in FIG. 2). Moving the sheath 19 forward causes it tomove over the basket structure 20, collapsing it into a compact, lowprofile condition for introducing into the heart region 12. Moving thesheath 19 rearward frees the basket structure 20, allowing it to springopen and assume the pretensed, radially expanded position shown in FIG.2. The electrodes are urged into contact against the surrounding hearttissue.

Further details of the basket structure are disclosed in pending U.S.patent application Ser. No. 08/206,414, filed Mar. 4, 1994, nowabandoned entitled "Multiple Electrode Support Structures."

In use, the electrodes 24 sense electrical events in myocardial tissuefor the creation of electrograms. The electrodes 24 are electricallycoupled to a process controller 32 (see FIG. 1A). A signal wire (notshown) is electrically coupled to each electrode 24. The wires extendthrough the body 18 of the probe 14 into a handle 21, in which they arecoupled to an external multiple pin connector 23. The connector 23electrically couples the electrodes to the process controller 32.

Alternatively, multiple electrode structures can be located epicardiallyusing a set of catheters individually introduced through the coronaryvasculature (e.g., retrograde through the aorta or coronary sinus), asdisclosed in PCT/US94/01055 entitled "Multiple Intravascular SensingDevices for Electrical Activity."

The ablation probe 16 (see FIG. 3) includes a flexible catheter body 34that carries one or more ablation electrodes 36. For the sake ofillustration, FIG. 3 shows a single ablation electrode 36 carried at thedistal tip of the catheter body 34. Of course, other configurationsemploying multiple ablation electrodes are possible, as described inpending U.S. patent application Ser. No. 08/287,310, filed Aug. 8, 1994,now U.S. Pat. No. 5,582,609 entitled "Systems and Methods for AblatingHeart Tissue Using Multiple Electrode Elements."

A handle 38 is attached to the proximal end of the catheter body 34. Thehandle 38 and catheter body 34 carry a steering mechanism 40 forselectively bending or flexing the catheter body 34 along its length, asthe arrows in FIG. 3 show.

The steering mechanism 40 can vary. For example, the steering mechanismcan be as shown in U.S. Pat. No. 5,254,088, which is incorporated hereinby reference.

A wire (not shown) electrically connected to the ablation electrode 36extends through the catheter body 34 into the handle 38, where it iselectrically coupled to an external connector 45. The connector 45connects the electrode 36 to a generator 46 of ablation energy. The typeof energy used for ablation can vary. Typically, the generator 46supplies electromagnetic radio frequency energy, which the electrode 36emits into tissue. A radio frequency generator Model EPT-1000, availablefrom EP Technologies, Inc., Sunnyvale, Calif., can be used for thispurpose.

In use, the physician places the ablation electrode 36 in contact withheart tissue at the site identified for ablation. The ablation electrodeemits ablating energy to heat and thermally destroy the contactedtissue.

According to the features of the invention, the process controller 32employs electrogram matching to automatically locate for the physicianthe site or sites potentially appropriate for ablation.

I. Electrogram Matching

The process controller 32 is operable to sense electrical events inheart tissue and to process and analyze these events to achieve theobjectives of the invention. The process controller 32 is alsoselectively operable to induce electrical events by transmitting pacingsignals into heart tissue.

More particularly, the process controller 32 is electrically coupled bya bus 47 to a pacing module 48, which paces the heart sequentiallythrough individual or pairs of electrodes to induce depolarization.Details of the process controller 32 and pacing module 48 are describedin copending U.S. patent application Ser. No. 08/188,316, filed Jan. 28,1994, now U.S. Pat. No. 5,494,042 and entitled "Systems and Methods forDeriving Electrical Characteristics of Cardiac Tissue for Output inIso-Characteristic Displays."

The process controller 32 is also electrically coupled by a bus 49 to asignal processing module 50. The processing module 50 processes cardiacsignals into electrograms. A Model TMS 320C31 processor available fromSpectrum Signal Processing, Inc. can be used for this purpose.

The process controller 32 is further electrically coupled by a bus 51 toa host processor 52, which processes the input from the electrogramprocessing module 50 in accordance with the invention to locatearrhythmogenic foci. The host processor 32 can comprise a 486-typemicroprocessor.

According to the invention, the process controller 32 operates in twofunctional modes, called the sampling mode and the matching mode.

In the sampling mode, the physician deploys the basket structure 20 inthe desired heart region 12. To assure adequate contact is made in thedesired region 12, the physician may have to collapse the basketstructure 20, rotate it, and then free the basket structure 20. Thedegree of contact can be sensed by the process controller 32 in variousways. For example, the process controller 32 can condition the pacingmodule 48 to emit pacing signals through a selected electrode 24 or pairof electrodes 24. The process controller 32 conditions the electrodes 24and processing module 50 to detect electrograms sensed by a desirednumber of the electrodes 24. The processing module can also ascertainthe desired degree of contact by measuring tissue impedance, asdescribed in copending patent application Ser. No. 08/221,347, filedMar. 31, 1994, now U.S. Pat. No. 5,598,818 and entitled "Systems andMethods for Positioning Multiple Electrode Structures in ElectricalContact with the Myocardium."

Once the basket structure 20 is properly positioned, the processcontroller 32 conditions the electrodes 24 and signal processing module50 to record electrograms during a selected cardiac event having a knowndiagnosis. In the sampling mode, the process controller 32 typicallymust condition the pacing module 48 to pace the heart until the desiredcardiac event is induced. Of course, if the patient spontaneouslyexperiences the cardiac event while the structure 20 is positioned, thenpaced-induction is not required.

The processor controller 32 saves these electrograms in the hostprocessor 52. The process controller 32 creates templates of selectedelectrogram morphologies by any conventional method, e.g., by having thephysician manually select representative electrogram morphologies. Atthe end of the sampling mode, the process controller 32 typically mustcondition the pacing module 48 to pace terminate the cardiac event, orthe physician may apply a shock to restore normal sinus rhythm.

The matching mode is conducted without altering the position of themultiple electrode structure 20 in the heart region 12, so that theelectrodes 24 occupy the same position during the matching mode as theydid during the sampling mode.

In the matching mode, the process controller 32 conditions the pacingmodule 48 to pace the heart in a prescribed manner without inducing thecardiac event of interest, while conditioning the signal processingmodule 50 to record the resulting electrograms. The process controller32 operates the host processor 52 to compare the resulting pacedelectrogram morphologies to the electrogram morphology templatescollected during the sampling mode. Based upon this comparison, the hostprocessor 52 generates an output that identifies the location of theelectrode or electrodes 24 on the structure 20 that are close to apotential ablation site.

A. The Sampling Mode

As before generally described, the process controller 32 operates in thesampling mode while the heart is experiencing a selected cardiac eventof known diagnosis and the basket structure 20 is retained in a fixedlocation in the region 12. In the illustrated and preferred embodiment,the selected event comprises an arrhythmia that the physician seeks totreat, for example, ventricular tachycardia (VT), or atrial tachycardia(AT), or atrial fibrillation (AF).

As FIG. 4A shows, during the sampling mode, the signal processing module50 processes the electrogram morphologies obtained from each electrodeduring the known cardiac event (designated for the purpose ofillustration as E1 to E3 in FIG. 4A). The electrograms may be recordedunipolar (between an electrode 24 and a reference electrode, not shown)or bipolar (between electrodes 24 on the structure 20).

The host processor 52 creates a digital, event-specific template for themorphology sensed at each electrode (designated for the purpose ofillustration as T1 to T3 in FIG. 4A). The event-specific templates T1 toT3 for each electrode E1 to E3 can be based upon electrogram morphologyfrom one heart beat or a specified number of heart beats. Theevent-specific template T1 to T3 for each electrode E1 to E3 can becreated by, for example, having the physician manually selectrepresentative electrogram morphologies.

If the arrhythmia event is not polymorphic, the template preferablycomprises one heart: beat and is updated beat by beat. Also preferably,though not essential, the starting point of the template should coincidewith the beginning of the depolarization and extend one beat from thatpoint. However, if the arrhythmia event under study is polymorphic, itmay be necessary to extend the template over several beats. For example,in bigeminy cases, the template should preferably extend over two beats.

The host processor 52 retains the set of event-specific templates T1 toT3 in memory. The processor 52 can, for an individual patient, retainsets of event-specific templates for different cardiac events. Forexample, a patient may undergo different VT episodes, each with adifferent morphology. The processor 52 can store templates for each VTepisode for analysis according to the invention. The templates can bedownloaded to external disk memory for off-line matching at a subsequenttime, as will be described later. Templates can also be generated basedupon mathematical modeling or empirical data and stored for latermatching for diagnostic purposes.

B. The Matching Mode

In the matching mode, the process controller 32 operates the pacingmodule 48 to apply pacing signals sequentially to each of the individualelectrodes. The pacing electrode is designated Ep in FIG. 4A.

The pacing signal induces depolarization, emanating at the location ofthe pacing electrode Ep. The process controller 32 operates the signalprocessing module 50 to process the resulting paced electrogrammorphologies sensed at each electrode (again designated E1 to E3 for thepurpose of illustration in FIG. 4A) during pacing by the selectedindividual electrode Ep. The processed paced electrograms are designatedP1 to P3 in FIG. 4A.

The paced morphology P1 to P3 at each electrode can be from one heartbeat or a specified number of heart beats, provided that the length ofthe morphologies P1 to P3 is not shorter than the length of theevent-specific templates Ti to T3 for the same electrodes E1 to E3obtained during the sampling mode.

Different conventional pacing techniques can be used to obtain the pacedmorphologies P1 to P3. For example, conventional pace mapping can beused, during which the pace rate is near the arrhythmia rate, butarrhythmia is not induced.

For reasons that will be explained later, conventional entrainment orreset pacing is the preferred technique. During entrainment pacing, thepacing rate is slightly higher than and the period slightly lower thanthat observed during the arrhythmia event, thereby increasing the rateof the induced arrhythmia event. Further details of entrainment pacingare found in Almendral et al., "Entrainment of Ventricular Tachycardia:Explanation for Surface Electrocardiographic Phenomena by Analysis ofElectrograms Recorded Within the Tachycardia Circuit," Circulation, vol.77, No. 3, March 1988, pages 569 to 580, which is incorporated herein byreference.

Regardless of the particular pacing technique used, the pacing stimulusmay be monophasic, biphasic, or triphasic.

In the matching mode, while pacing at an individual one of theelectrodes Ep, the host processor 52 compares the paced morphology P1 toP3 obtained at each electrode E1 to E3 to the stored event-specifictemplate T1 to T3 for the same electrode E1 to E3. The comparisons(which are designated C1 to C3 in FIG. 4A) can be performed by usingmatched filtering or correlation functions, as will be described later.

Alternatively, the paced morphologies P1 to P3 can be retained in memoryor downloaded to external disk memory for matching at a later time. Toaccommodate off-line processing, the host processor 52 preferablyincludes an input module 72 for uploading pregenerated templates and/orpaced morphologies recorded at an earlier time. The input module 72allows templates and paced morphologies to be matched off-line by thehost processor 52, without requiring the real time presence of thepatient. Alternatively, recorded paced morphologies can be matched inreal time using templates generated earlier. The pregenerated templatescan represent "typical" biopotential events based upon either real,empirical data, or mathematical models for diagnostic purposes, orreflect earlier biopotential events recorded for the same patient or fora patient having the same or similar prognosis.

For each pacing electrode Ep(j), the host processor 52 generates amatching coefficient M_(COEF)(i) for each electrode E(i) from thecomparison C(i) of the pacing morphology P(i) to the template morphologyT(i) for the same electrode E(i). Preferably, both j and i=1 to n, wheren is the total number of electrodes on the three dimensional structure(which, for the purpose of illustration in FIG. 4A, is 3).

The value of the matching coefficient M_(COEF)(i) is indicative for thatelectrode E(i) how alike the pacing morphology P(i) is to theevent-specific template T(i) for that electrode E(i). The value ofM_(COEF)(i) for each electrode E(i) varies as the location of the pacingelectrode Ep(j) changes. Generally speaking, the value of the matchingcoefficient M_(COEF)(i) for a given electrode E(i) increases in relationto the closeness of the pacing electrode Ep(j) to the arrhythmogenicfoci. In the illustrated and preferred embodiment (as FIG. 4A shows),while pacing at an individual one of the electrodes Ep(j), the hostprocessor 52 generates from the matching coefficients M_(COEF)(i) foreach electrode E(i) an overall matching factor M_(PACE)(j) for thepacing electrode Ep(j). The value of the overall matching factorM_(PACE)(j) for the pacing electrode Ep(j) is indicative of how alikethe overall propagation pattern observed during pacing at the electrodeEp(j) is to the overall propagation pattern recorded on the associatedevent-specific templates.

The process controller 32 operates the pacing module 48 to apply apacing signal sequentially to each electrode Ep(j) and processes andcompares the resulting electrogram morphologies at each electrode E(i)(including Ep(j)) to the event-specific templates, obtaining thematching coefficients M_(COEF)(i) for each electrode E(i) and an overallmatching factor M_(PACE)(j) for the pacing electrode Ep(j), and so on,until every electrode E(i) serves as a pacing electrode Ep(j).

M_(PACE)(j) for each pacing electrode can be derived from associatedmatching coefficients M_(COEF)(i) in various ways.

For example, various conventional averaging techniques can be used. Forexample, M_(PACE)(j) can be computed as a first order average(arithmetic mean) of M_(COEF)(i) as follows: ##EQU1## where i=1 to n; oras a weighted arithmetic mean, as follows:

    M.sub.PACE(j) =ΣW(i)M.sub.COEF(i)

where i=1 to n; ΣW(i)=1. If W(i)=1/n, for each i, then the arithmeticmean is obtained.

Generally speaking, the value of the overall matching factor M_(PACE)(j)increases in relation to the proximity of the particular pacingelectrode Ep(j) to a potential ablation site.

By way of overall explanation, for VT, the site appropriate for ablationtypically constitutes a slow conduction zone, designated SCZ in FIG. 4B.Depolarization wave fronts (designated DWF in FIG. 4B) entering the slowconduction zone SCZ (at site A in FIG. 4B) break into errant, circularpropagation patterns (designated B and C in FIG. 4B), called "circusmotion." The circus motions disrupt the normal depolarization patterns,thereby disrupting the normal contraction of heart tissue to cause thecardiac event.

The event-specific templates T(i) record these disrupted depolarizationpatterns. When a pacing signal is applied to a slow conduction zone, thepacing signal gets caught in the same circus motion (i.e., paths B and Cin FIG. 4B) that triggers the targeted cardiac event. A large proportionof the associated pacing morphologies P(i) at the sensing electrodesE(i) will therefore match the associated event-specific templates P(i)recorded during the targeted cardiac event. This leads to a greaternumber of larger matching coefficients M_(COEF)(i) and thus to a largeroverall matching factor M_(PACE)(j).

However, when a pacing signal is applied outside a slow conduction zone,the pacing signal does not get caught in the same circus motion. Itpropagates free of circus motion to induce a significantly differentpropagation pattern than the one recorded in the templates T(i). A largeproportion of the pacing morphologies P(i) at the sensing electrodesE(i) therefore do not match the event-specific templates T(i). Thisleads to a smaller number of larger matching coefficients M_(COEF)(i)and thus to a smaller overall matching factor M_(PACE)(j).

This is why the overall matching factor M_(PACE)(j) becomes larger thecloser the pacing electrode Ep(j) is to the slow conduction zone, whichis the potential ablation site. The difference in propagation patternsbetween pacing inside and outside a slow conduction zone is particularlypronounced during entrainment pacing. For this reason, entrainmentpacing is preferred.

Ablating tissue in or close to the slow conduction zone preventssubsequent depolarization. The destroyed tissue is thereby "closed" as apossible path of propagation. Depolarization events bypass the ablatedregion and no longer become caught in circus motion. In this way,ablation can restore normal heart function.

The matching of pacing morphologies P(i) to template morphologies T(i)to create the matching coefficient M_(COEF)(i) and the overall matchingfactor M_(PACE)(j) can be accomplished in various ways. According to theinvention, the host processor 52 can employ pattern matching; symmetrymatching; matched filtering; cross correlation; or norm of thedifference techniques. The following provides an overview of each ofthese techniques.

1. Pattern Matching

FIG. 5 diagrammatically shows a pattern matching technique that embodiesfeatures of the invention.

The pattern matching technique matched filters the template T(i) foreach electrode E(i) using the same template flipped left to right withrespect to time, Tflip(i), as coefficients of the matched filter. FIG.6B shows a representative template T(i) for a given electrode E(i). FIG.6C shows Tflip(i), which is the template T(i) (shown in FIG. 6B) flippedright to left. FIG. 6E shows a matched filtered output MT(i), which hadT(i) (FIG. 6B) as input and Tflip(i) (FIG. 6C) for the same electrodeE(i) as coefficients of the matched filter. As FIG. 6E shows, thematched filtered output MT(i) is, for the electrode E(i), a sequence ofalternating maximums and minimums, with their values marking a firstpattern employed by this technique.

The pattern matching technique also matched filters the pacedelectrogram P(i) for each electrode E(i) using an identical matchedfilter as the one described above. FIG. 6A shows a representative pacedelectrogram P(i) for the given electrode E(i). FIG. 6D shows the matchedfiltered output MP(i), using Tflip(i) shown in FIG. 6C as the matchedfiltered coefficients. Like MT(i), the matched filtered output MP(i) is,for each electrode E(i), a sequence of alternating maximums andminimums, which are used to construct a second pattern.

The pattern matching technique detects the maximums and minimums for thematched filtered template outputs MT(i) and those of MP(i). The patternmatching technique places the maximums and minimums in two odd-length,L-sized model vectors within the largest excursions at position ##EQU2##where L is the total number of local extremes of MT(i) and MP(i). Thepattern matching technique computes the norm of the difference betweenthe MP-pattern and the corresponding MT-pattern shifted by an amount, P,that varies from -K to K, where K> L/2. The maximum number ofcomparisons for n electrodes will be n comparisons for each pacingelectrode. Alternatively, one can shift the MP-patterns as justdescribed, keeping the corresponding MT-patterns fixed. The largestexcursions are placed in the centers of the template and paced vectors.##EQU3## where r=1 to 3 and p=-K to K.

The minimum of the above is used as the matching coefficient for thesequence of norms (M_(COEF)(i)), i.e.,:

    M.sub.COEF(i) =min(norm.sub.(i p))

for p=-K to K.

The minimum norms of the electrodes are averaged by an appropriateweighted average algorithm (as above discussed). This yields the overallmatching factor M_(PACE)(j) for each pacing electrode Ep(j), i.e.,##EQU4##

2. Symmetry Matching

FIG. 7A shows a symmetry matching technique that embodies features ofthe invention.

The symmetry matching technique matched filters the paced electrogramP(i) for each electrode E(i) using Tflip(i) as coefficients of thematched filter. Each filter output is tested with respect to the largestexcursion or extreme from baseline (EXC_(MAX)), the sign (positive ornegative) of EXC_(MAX), and a symmetry index (SYM), where: ##EQU5##except when EXC_(MAX) <0, then SYM=1;

where N equals the number of local extremes to the left of EXC_(MAX)(which is also equal to the number of local extremes situated to theright of EXC_(MAX) (see FIG. 7B).

The technique first determines whether EXC_(MAX) >0 (that is, whether itis positive). If EXC_(MAX) is not positive (i.e, SYM=1.0), the techniquedeems that a poor match has occurred on this criteria alone. IfEXC_(MAX) is positive, the technique goes on to compute the symmetryindex SYM and compares SYM to a symmetry threshold (SYM_(THRESH)). IfSYM≦SYM_(THRESH) ' the technique deems that a good match has occurred.In the preferred embodiment, SYM_(THRESH) =0.2 (for perfect symmetry,SYM=0.0).

Similar electrograms will create a matched filtered output having apositive largest excursion. As the degree of similarity between the twoelectrograms increases, the matched filtered output will becomeincreasingly more symmetric about this positive absolute maximum. Thescoring factor is created for each electrogram comparison, where thescoring factor M_(COEF)(i) =1-SYM. The scoring factors based upon SYMare converted to an overall matching factor M_(PACE)(j) for each pacingelectrode Ep(j), as previously described. The pacing electrode Ep(j)creating the highest overall matching factor is designated to be closeto a potential ablation site.

For example, FIG. 6E shows the matched filtered output MT(i) of thetemplate electrogram of FIG. 6B and its left-to-right flippedcounterpart of FIG. 6C. The electrogram of FIG. 6B is, in effect,matched filtered against itself, and the symmetry matching techniquedetects this. FIG. 6E shows a largest excursion that is positive and anoutput that is perfectly symmetric about the positive absolute maximum.A perfect scoring factor M_(COEF)(i) Of 1.0 would be assigned.

Refer now to FIG. 6D, which is the matched filtered output MP(i) of theelectrogram of FIG. 6A and the flipped template in FIG. 6C. These aredifferent, yet similar electrograms. The symmetry matching techniquedetects this close similarity. FIG. 6D shows a positive largestexcursion, and the output is relatively symmetric about this positiveabsolute maximum. A good scoring factor M_(COEF)(i) Of, for example, 0.9would be assigned.

Refer now to FIG. 8C, which is the matched filtered output of theelectrogram of FIG. 6A using the flipped template shown in FIG. 8B ascoefficient of the matched filter. It can be seen that the electrogramshown in FIG. 8A has a morphology quite different than that shown inFIG. 6A. The symmetry matching technique detects this difference. FIG.8C shows a negative largest excursion and an output that is notsymmetric about this absolute maximum. A poor scoring factor M_(COEF)(i)of zero would be assigned.

3. Matching Against Dirac Pulse

FIG. 9 shows a technique matching against Dirac pulse that embodiesfeatures of the invention.

This matching technique employs a whitening algorithm to first filterthe template electrograms and the paced electrograms. The whiteningfilter transforms so-called colored noise, which can be 60-Hz (or 50-Hz)interference, or motion or muscular artifacts of the patient, to whitenoise.

The technique matched filters the whitened paced electrogram for eachelectrode using the left-right flipped, whitened template for thatelectrode as coefficients of the matched filter. Ideally, exactlymatched, whitened electrograms will produce an output that equals aDirac pulse. Therefore, each filter output is compared to a Dirac pulse.An algorithm scores the similarity for each electrode.

The pacing electrode whose whitened, matched filtered output mostclosely resembles a Dirac pulse is designated to be close to a potentialablation site.

4. Cross Correlation Technique

FIG. 10 shows a cross correlation technique that embodies features ofthe invention.

This technique uses an appropriate algorithm to calculate for eachelectrode the cross correlation function between the templateelectrogram and the paced electrogram. For identical electrograms, thelargest excursion of the cross correlation function will equal 1.0.

Various conventional methods for determining the cross correlationfunction can be used. For example, for M pairs of data {x(m), y(m)},where x(m) is the template electrogram and y(m) is the pacedelectrogram, the correlation function can be calculated as follows:##EQU6## where m=1 to M; -M≦k≦M, and x and y are the means of thesequences {x} and {y}.

M_(COEF)(i) is equal to the largest excursion of the sequence {rxy(k)}computed for the individual electrode E(i) (i.e., the largest excursioncan be either negative or positive, depending upon the degree ofintercorrelation).

The pacing electrode Ep(j) having an overall matching factor M_(PACE)(j)closest to 1.0 is designated to be close to a potential ablation site.Additional information may be contained in the shift parameter k foreach electrode.

For example, FIG. 11A shows the cross correlation function for theelectrograms of FIG. 6A and FIG. 6B. These electrograms are quitesimilar, and the cross correlation technique detects this. The largestexcursion of the cross correlation function in FIG. 11A is near 1.0(i.e., it is 0.9694).

Refer now to FIG. 11B, which shows the cross correlation function forthe unlike electrograms shown in FIGS. 6A and 8A. The cross correlationtechnique detects this lack of similarity. The largest excursion in FIG.11B is negative (i.e., it is -0.7191).

5. Norm of the Difference Technique

FIG. 12 shows a norm of the difference technique that embodies featuresof the invention.

This technique normalizes, for each electrode, the template electrogramwith respect to the absolute value of its largest excursion frombaseline. This technique also normalizes, for each electrode, the pacedelectrogram with respect to the largest excursion from baseline. Thetechnique then calculates, for each electrode, the norm of thedifference between the template electrogram and the paced electrogram.The norm will decrease in proportion to the similarity of theelectrograms.

For example, FIG. 13A is the difference between the similar electrogramsshown in FIGS. 6A and 6B, after each was normalized with respect to itslargest excursion. This technique detects the similarity with arelatively small norm of the difference (i.e., it is 0.9620).

Refer now to FIG. 13B, which is the difference between the dissimilarelectrograms shown in FIGS. 6A and 8A, after each was normalized withrespect to its largest excursion. This technique detects the lack ofsimilarity with a relatively high norm of the difference (i.e., it is2.4972).

The technique preferably uses a weighted averaging algorithm to average,for each pacing electrode, the norm of the differences for all recordingelectrodes. The pacing electrode having the smallest average norm of thedifferences is designated the appropriate place to ablate.

The electrograms may or may not be filtered before analysis. A 1 to 300Hz bandpass filter may be used for filtering. If a filter is used toreduce the noise for an electrogram that is used as a template, the samefilter must also be used for the paced electrograms, since filtering mayalter the electrogram morphology.

The electrograms might need to be aligned prior to processing. Anycolumnar alignment technique can be used. For example, the electrogramscould be aligned about the point of largest positive slope.

The implementation of the system 10 described herein is based largelyupon digital signal processing techniques. However, it should beappreciated that a person of ordinary skill in this technology area caneasily adapt the digital techniques for analog signal processing.

The output signal y(t) of an analog matched filter is given by theanalog convolution:

y(t)=x(t)*Tflip(t);

where Tflip(t)=EG(T-t), which constitutes a left-right flipped replicaof the electrogram template EG(t) that has the period T.

Physically, an analog matched filter can be implemented with analogintegrators and adders. Also, optical realizations of such filters canbe implemented, for example, by using optical slots to represent thetemplate. After optical conversion, the input signal is passed throughthe optical slot. The average light intensity behind the optical slotplane is maximal when the shape of the optically converted input signalmatches the shape of the slot. An optical sensor can measure the averagelight intensity and output a signal that represents the matchedcoefficient M_(COEF)(i).

C. Location Output Isolation and Verification

In one implementation, the host processor 52 sets a match targetN_(match), which numerically establishes a matching factor M_(PACE)(j)at which a high probability exists that the pacing electrode is close toa potential ablation site. In a preferred implementation, N_(MATCH)=0.8. When M_(PACE)(j) >N_(MATCH), the host processor 52 deems thelocation of the pacing electrode Ep(j) to be close to a potential sitefor ablation. When this occurs (as FIG. 4 shows), the host processor 52transmits a SITE signal to an associated output display device 54 (seeFIG. 1A). Through visual prompts, the display device 54 notifies thephysician of the location of the pacing electrode Ep(j) and suggeststhat the location as a potential ablation site. When more two or moreM_(PACE)(j) >N_(MATCH), the host processor 52 sorts to locate theM_(PACE)(j) having the highest value. In this instance, the hostprocessor 52 deems the pacing electrode Ep(j) with the highestM_(PACE)(j) to be the one having the highest likelihood for being closeto a potential ablation site and transmits the SITE signal accordingly.

In the illustrated and preferred embodiment, the process controller 32provides iterative pacing and matching using different pacing andmatching techniques. Using different pacing-and-compare techniquesallows the comparison of the location output from one technique with thelocation output from one or more different techniques. Using iterativepacing and matching, the process controller 32 and the host processor 52confirm and cross-check the location output to verify its accuracybefore ablation. The host processor 52 can also rely upon alternativediagnostic techniques to analyze the biopotential morphology.

In the illustrated and preferred embodiment (see FIG. 1B), the system 10also includes a roving pacing probe 68 usable in tandem with the basketstructure 20 to generate and verify the location output.

1. Iterative Pacing

In the illustrated and preferred embodiment (see FIG. 1B), the processcontroller 32 includes a module 60 that allows the physician to selectamong different types of pacing techniques. The different pacingtechniques allow the physician to conduct both global and localized siteidentification, with and without inducing the abnormal cardiac event.

At least one technique is appropriate for pacing a large tissue regionto identify a subregion close to a potential ablation site, without theneed to induce an abnormal cardiac event. In a preferred implementation,the process controller 32 first conditions the pacing module 48 in themode to conduct pace mapping. Pace mapping uses all electrodes 24 on thestructure 20 in sequence as the pacing electrode, and does not inducethe cardiac event. Based upon pace mapping, the process controller 32obtains a location output that points to a general subregion that isclose to a potential ablation site.

Once the general region is identified, another pacing technique can beemployed to more narrowly define the location of the potential ablationsite within the general region. In a preferred implementation, theprocess controller 32 conditions the pacing module 48 in the matchingmode to carry out entrainment or reset pacing, using the electrodes inthe general subregion as the pacing electrodes. Entrainment or resetpacing in this subregion overdrives the arrhythmia, and providesenhanced differentiation of slow conduction zones. The processcontroller 32 thereby obtains a location output that is more localizedwith respect to the potential ablation site.

2. Iterative Matching

In the illustrated and preferred embodiment (see FIG. 1B), the processcontroller 32 also includes a module 62 that allows the physician toselect more than one matching technique during iterative pacing. Forexample, the process controller 32 may, during pace mapping orentrainment/reset pacing, compare the templates to the pacedelectrograms by first pattern matching, then by symmetry matching, andthen by norm of the difference. In this way, the process controller 32determines the uniformity of the location output among the differentmatching techniques. The correspondence of the location outputs confirmstheir reliability.

3. Cross-Check Using Alternative Diagnostic Techniques

In the preferred embodiment, the process controller 32 is alsoelectrically coupled by a bus 64 to a diagnostic module 66. Under thecontrol of the process controller 32, as selected by the physician, thediagnostic module 66 conducts one or more alternative analyses of heartactivity to cross check or verify the output location that the processcontroller 32 generates based upon electrogram matching.

In the illustrated embodiment (see FIG. 1B), the module 66 determinesthe fractionation of the paced electrograms. The degree of fractionationcan be used as a cross-check that the physician can employ tocross-check and verify the output location or locations that the processcontroller 32 yields when operated in the matching mode.

4. The Roving Pacing Probe

Using the above iterative pacing and matching techniques, the locationoutput may comprise a single electrode 24 or several electrodes 24 in alocalized region of the structure 20. In the illustrated and preferredembodiment (see FIG. 1B), the system 10 further includes a roving pacingprobe 68 that can be deployed in the heart region 12 while the multipleelectrode structure 20 occupies the region 12. The roving probe 68 iselectrically coupled to the pacing module 48 to emit pacing signals.

In use, once the process controller 32 generates the output location orlocations using the electrodes 24 to pace the heart, the physicianpositions the roving electrode probe 68 within the localized region nearthe output location electrode or electrodes 24. The process controller32 preferably includes a homing module 70 to aid the physician inguiding the roving electrode probe 68 in the localized region within thestructure 20. Systems and methods for operating the homing module 70 aredisclosed in copending patent application Ser. No. 08/320,301, filedOct. 11, 1994, now abandoned and entitled "Systems and Methods forGuiding Movable Electrode Elements Within Multiple ElectrodeStructures", which is incorporated herein by reference.

The process controller 32 conditions the pacing module 48 to emit pacingsignals through the roving pacing probe 68 to pace the heart in thelocalized region, while the electrodes 24 record the resultingelectrograms. By pacing this localized region with the roving pacingprobe 68, while comparing the paced electrograms with the templates, theprocess controller 32 provides the capability of pacing and comparing atany location within the structure 20. In this way, the processcontroller 32 generates as output a location indicator that locates asite as close to a potential ablation site as possible. Of course,iterative pacing and matching techniques, as above described, can bepracticed using the roving pacing probe 68.

Due to the often convoluted and complex contours of the inside surfaceof the heart, the basket structure 20 cannot contact the entire wall ofa given heart chamber. The preferred implementation of the system 10 (asFIG. 1B shows) therefore deploys the roving pacing probe 68 outside thestructure to pace the heart in those wall regions not in contact withthe electrodes 24. The roving pacing probe 68 can also be deployed whilethe basket structure 20 occupies the region 12 to pace the heart in adifferent region or chamber. In either situation, the electrodes 24 onthe structure 20 record the resulting paced electrograms for comparisonby the process controller 32 to the templates. The process controller 32is thus able to generate an output identifying a location close to apotential ablation site, even when the site lies outside the structure20 or outside the chamber that the structure 20 occupies.

Acting upon the location output generated in accordance with theinvention, the physician deploys the ablation electrode 36 to thelocation of the pacing electrode Ep(j) to conduct the ablation (as FIG.1A shows). The homing module 70 (as already described and as shown inFIG. 1B) can also be used to aid the physician in deploying the ablationelectrode 36 to the designated site, as disclosed in copending patentapplication Ser. No. 08/320,301, now abandoned filed Oct. 11, 1994, andentitled "Systems and Methods for Guiding Movable Electrode ElementsWithin Multiple Electrode Structures", which is incorporated herein byreference.

It should be appreciated that the system 10 is not limited to thediagnosis and treatment of arrhythmia events. The system 10 can be usedin the sampling mode, for example, to create templates while the heartis in sinus rhythm. In the matching mode, the heart can be paced atsinus rhythm rates and the paced electrograms compared to the templatesto detect abnormal activation patterns associated with other forms ofheart disease or to identify the presence of accessory pathways.

D. Time-Sequential Analysis In the illustrated and preferred embodiment,the template electrograms at all electrodes 24 are recorded during thesame time interval. Likewise, the pacing electrograms for each pacingelectrode Ep(j) are recorded at all electrodes 24 during the same timeinterval. This technique requires the process controller 32 to haveparallel processing channels equal in number to the number of electrodes24 conditioned to record the electrograms.

For example, it is typically desired to record electrogram informationfrom thirty-two (32) electrode pairs when analyzing monomorphic VT. Whenthe electrograms are recorded over the same time interval, the processcontroller 32 must be capable of handling thirty-two (32) parallelchannels of information.

In an alternative embodiment, the process controller 32 can be operatedin a time-sequential recording mode. In this mode, the processcontroller 32 records electrograms, either to create a template or tocreate paced electrograms for matching, at different time intervals. Inthis mode, the process controller 32 consolidates the time-sequentialelectrograms for composite analysis, as if the electrograms wererecorded during the same time intervals.

The time-sequential mode can be used when the waveshapes of theelectrograms to be analyzed are generally the same during each heartbeat. For example, monomorphic VT is characterized by suchtime-invariant electrogram waveshapes. The time-sequential mode allowsthe physician to condition the process controller 32 to record timeinvariant electrograms in numbers greater than the number of processingchannels that the process controller 32 has.

For example, if the process controller 32 can only accommodate twenty(20) channels of data at a given time, the time-sequential modenevertheless allows information from thirty-two (32) electrograms to berecorded and processed.

FIG. 21 shows the time-sequential mode of operation in diagrammatic flowchart form. During a first time interval TI(1), the time-sequential modesimultaneously records electrograms at first electrode sites ES(1). InFIG. 21, the first electrode sites ES(1) number twenty (20) and aredesignated E(1) to E(20). The electrograms for the first site electrodesE(1) to E(20) are retained for the first time interval TI(1). FIG. 22Ashows representative electrograms recorded at E(1) during TI(1). FIG.22B shows a representative electrogram recorded at E(2) during TI(1).

During a second time interval TI(2), the time-sequential modesimultaneously records electrograms at second electrode sites, at leastone of which is an electrode site used during the first time intervalTI(1). FIG. 21 identifies E(1) as the common electrode site. E(21) toE(32) comprise the remaining electrodes in ES(2). FIG. 22C showsrepresentative electrograms recorded at the common electrode site E(1)during TI(2). FIG. 22D shows representative electrograms recorded at theadditional electrode site E(21) during TI(2).

In a preferred implementation, the process controller 32 conditions thefirst electrode sites ES(1) for recording and records electrograms fromthese sites for TI(1)=4 seconds. The process controller 32 thenautomatically conditions the second electrode sites ES(2) for recordingand records electrograms from these sites for TI(2)=4 seconds. Thus,over a time-sequenced interval of eight (8) seconds, the processcontroller 32 has recorded electrograms at thirty-two (32) electrodesites, which is the number desired for analysis.

The time-sequential mode determines the time difference TD between theelectrograms for E(1) at TI(1) and TI(2). FIG. 22C shows TD.

The time-sequential mode time-aligns E(l) at TI(2) with E(1) at TI(1) byleft-shifting E(1) at TI(2) by TD. FIG. 23C shows the representativeelectrograms recorded at E(1) during TI(2) after time-alignment with theelectrograms recorded at E(1) during TI(1), which are shown in FIG. 23A.

The time-sequential mode also left-shifts the electrograms E(21) throughE(32) by the same amount TD. FIG. 23D shows the representativeelectrograms recorded at E(21) during TI(2) after time-alignment withthe electrograms recorded at E(2) during TI(1), which are shown in FIG.23 B.

In this way, the time-sequential mode creates the electrogram compositeEC, which consists of the time-registered electrograms E(1) to E(32)taken at TI(1) and TI(2). The time-alignment process of creating theelectrogram composite signal EC can be done manually by the physician,by interacting with the display device 54. Preferably, the hostprocessor 52 automatically analyzes the signals, computes TD, andaccomplishes the time-alignment to create the composite electrogram EC.Alternatively, TD need not be computed. The physician or the operatorcan make use of any time-assignment method to align the signals based onthe information contained in the common channels E(1). An example ofuseful information is the location of the maximal slopes of E(1). Ofcourse, this algorithm can be automatically implemented and executed.

Though taken at different time intervals TI(1) and TI(2), thetime-aligned electrogram composite EC can be analyzed in the same manneras electrograms taken simultaneously during the same time interval. Inthe context of the system 10 described herein, the electrogram compositeEC can be used to create the electrogram template, or to create pacedelectrograms for comparison with an electrogram template, or aselectrograms for any other diagnostic purpose.

For example, using the above described time-sequential methodology,virtually all types of signals derived from biological events can beprocessed, such as electrocardiograms, tissue biopotential signals,pressure waves, electrogastrograms, electromyograms,electroencephalograms, impedance measurements, and temperaturemeasurements.

II. Endocardially Paced Electrocardiograms

A. Electrocardiogram Matching

In the preceding embodiments, the endocardially positioned basketstructure 20 both paces and senses the resulting electrograms. In analternative implementation, the process controller 32 can condition thepacing module 48 in the sampling mode to pace the heart to induce adesired cardiac event, using individual or pairs of electrodes 24 on thebasket structure 20 deployed in the heart region 12 (as alreadydescribed), while creating templates of the resulting electrocardiogramsrecorded by the processing module 50 from body surface electrodeselectrically coupled to the process controller 32.

In this implementation, during the matching mode, the process controller32 paces the heart with the individual or pairs of endocardialelectrodes 24 positioned on the structure 20 in the heart region 12. Theresulting paced electrocardiograms are recorded by the same body surfaceelectrodes (located in the same position as during the sampling mode)and compared to the electrocardiogram templates in the manner abovedescribed.

In this implementation, the process controller 32 generates the locationoutput based upon comparing the electrocardiogram sample templates withendocardially paced electrocardiograms.

B. Electrocardiogram Time Delays

Endocardially paced electrocardiograms can also be used to identifyregions of slow conduction.

In this implementation, while the process controller 32 conditions thepacing module 48 to pace the heart with the individual or pairs ofelectrodes 24 positioned on the structure 20 endocardially in the heartregion 12, the resulting endocardially paced electrocardiograms arerecorded by body surface electrodes coupled to the process controller32. From the endocardially paced electrocardiograms, the processcontroller 32 measures the time difference between the pacing signal andthe onset of the Q-wave to detect slow conduction regions (characterizedby abnormally large time delays).

Preferably, the process controller 32 generates maps displaying iso-timedelay regions based upon these endocardially paced electrocardiograms,to further aid in the location of the slow conduction region.

C. Characterizing Tissue Morphology

Time delays obtained from endocardially paced electrocardiograms canalso characterize heart tissue morphology.

In this implementation, the body surface electrodes recordelectrocardiograms while the pacing module 48 paces the heart with theindividual or pairs of electrodes 24 positioned on the structure 20 inthe heart region 12. The pacing module 48 first paces the heart at ornear normal sinus rhythm rates. The process controller 32 registers thetime delays recorded from the resulting electrocardiograms. The pacingmodule 48 next paces the heart at an increased rate, e.g., at or near anarrhythmia rate. The process controller 32 registers the resulting timedelays from the resulting electrocardiograms.

The process controller 32 compares the paced sinus rate time delays withthe paced arrhythmia rate time delay. The location of the pacingelectrodes where the time delays shortened as the pacing rate increasedare near regions of healthy tissue. The location of pacing electrodeswhere the time delays lengthened as the pacing rate increased are nearregions of ischemic tissue. The process controller 32 preferablygenerates iso-display maps showing the distribution of the time delaydifferences, thereby aiding the physician in differentiating betweenregions of healthy and ischemic tissue.

III. Pacing Artifact Removal

Pacing artifacts in the pacing electrograms may be eliminated byconventional techniques to better discern the initial point ofdepolarization. However, in the illustrated and preferred embodiment,the process controller 32 includes a filter 56 (see FIG. 4) that removesthe pacing artifact for this purpose without otherwise altering themorphology of the electrogram. The operation of the filter 56 may vary.

A. Nonlinear Filter

In the preferred embodiment, the filter 56 implements a nonlinearsorting algorithm of the type shown in FIG. 14A.

FIG. 14B shows a representative implementation and filter output for thealgorithm in diagrammatic form.

The algorithm establishes a sample window. The sample window has apredetermined length (WL), expressed in terms of the number of discretesample points the window contains. The predetermined length (WL) of thesample window takes into account the length (AL) of the pacing artifact,which is expressed in terms of the number of sample points thatencompass the pacing artifact. Preferably, the window length WL is anodd number.

If WL is significantly smaller than twice AL, the sorting algorithm willnot serve to eliminate the pacing artifact to the extent necessary toaccurately discern the initial point of depolarization. There is,however, a limitation placed upon how large WL is relative to the sizeof AL. When WL is significantly larger than twice AL, the morphology ofthe electrogram will be distorted by being spread out with respect totime.

It is believed that the sample window length should preferably be atleast twice the pacing artifact length. Most preferably, WL>2AL+k, wherek=1 to WL/2. k is an additive amount that optimizes the elimination ofthe artifact without time distortion.

The algorithm advances the sample window along the electrogram, taking asuccession of boxcar samples, X(n), where n=1 to WL. The algorithm sortsthe sample values X(n) in the window from smallest value to largestvalue. The sorted permutation is the sequence {X(p n!)}, where {p n!} isa permutation of {n} resulting from the sorting process, and where n=1to WL. The algorithm selects one of the sort positions p f! according toprescribed criteria, where f=1 to WL. The selection criteria will bediscussed in greater detail later.

The algorithm outputs the sample value X(p f!) contained in the selectedsort position, which constitutes the filter output for the boxcarsample. The algorithm outputs X(p f!) and advances the window forward intime one sample point.

The algorithm repeats the sorting process, generating a filter outputfor each boxcar sample and advancing the window, until the entireelectrogram has been processed. The algorithm then plots the filteroutputs with respect to time, which constitutes the filteredelectrogram.

EXAMPLE (Nonlinear Filtering)

For example, given WL=5, the sequence of samples values X(n) is:##STR1##

The sequence of sample values X(1 to 5) constitutes the boxcar sample.

The algorithm sorts the sequence X(1 to 5) in increasing numericalvalue, or

X(2)<X(1)<X(5)<X(4)<X(3).

The algorithm establishes the sort positions p(n) based upon thispermutation, or ##STR2##

The algorithm selects a sort position p(f) according to prescribedcriteria. The criteria for selecting the sort position takes intoaccount the length of the artifact AL, as will be discussed later. Inthe preferred embodiment, the criteria specifies the sort positionrelative to the other sort positions. In this implementation, (f) isexpressed as a position (z) of WL positions, i.e., p(z/WL), where WL isthe size of the sort window. The position z is selected taking intoaccount AL, and, more particularly, z should increase as AL decreases.

For example, for WL=5, if z=3, then p(3/5) means that X(p(3)) replacesx(3) in the output sequence. The value X(p(3)) is 6, which becomes thefilter output for this boxcar sample, based upon the selected sortposition criteria.

In this particular case, p(3/5) criteria actually implements a medianfilter. For a given window, the following sort position z constitutesthe median ##EQU7## where: 1<z<WL, and

the expression: ##EQU8## represents the integer part of: ##EQU9##

For example 3.9!=3, just as 3.1!=3.

Further details on median filtering techniques are disclosed in "VLSIArray Processors" by S. Y. Kung (Prentice Hall, (1991).

Alternatively, if the selected sort position is p(4/5), the valueX(p(4)) is 8, which becomes the nonlinear, non-median filter output forthis boxcar sample, based upon the selected sort position criteria. Thiscorresponds to x(4) of the output sequence.

The algorithm advances the window one sample at a time, sorting thesample enclosed within the window, and generating a filter output basedupon the sort criteria, and so on until the entire electrogram has beenfiltered.

In the preferred embodiment, the algorithm keeps the timing of filteroutput in sequence with the timing of the electrogram by retaining thevalue of edge samples, so that the number of filter outputs equal thenumber of electrogram samples. The number of edge values retained, ofcourse, depends upon the size of the sample window WL.

More particularly, the algorithm retains a prescribed number, y₁, ofbeginning sample values a number, y₂, of ending sample values, arrangingthe filter output between the prescribed number of beginning and endingsample values to keep the filter output arranged with respect to time insequence with the derived biological signal. In the preferredimplementation,

    y.sub.1 =z-1

and

    y.sub.2 =WL-z

FIG. 14B shows the filtering of ten sample points (4 2 7 5 1 10 3 8 9 6)in accordance with the above described technique. The window length WLin FIG. 14B is 5, and the sort criteria is median filtering, i.e.p(3/5). FIG. 14B shows the retention of the edge samples, two samples (4and 2) at the front edge (y₁ =z-1 or 3-1=2) and two samples 9 and 6 atthe rear edge (y₂ =WL-z or 5-3 =2). FIG. 14B also shows the filteroutputs (4 5 5 5 8 8) between the edge samples, with the sorted samplesappearing to the right of the filter outputs.

FIG. 14C shows the filtering of the same ten sample points (4 2 7 5 1 103 8 9 6), with the same window length WL of 5, but with a non-mediansort criteria p(4/5). FIG. 14C shows the retention of the edge samples,three samples (4, 2, 7) in at the front edge (y₁ =z-1 or 4-1=3) and onesample 6 at the rear edge (y₂ =WL-z or 5-4=1). FIG. 14C shows the filteroutput for the p(4/5)-criteri-on: (5 7 7 8 9 9) between the edgesamples.

The selection of the sort position p(f) takes into account themorphology of the pacing artifact in terms of the length of the artifactAL, expressed in terms of the number of sample points that encompass it.The percentage value of f should increase as the artifact length ALdecreases, or, given a constant WL, z should increase as AL decreases.

EXAMPLE (Sort Position Selection Criteria)

FIG. 15A shows a simulated pacing artifact where AL is 5 and the widthof the highest peak is 3. FIG. 15B shows the filtered output for p(2/5);FIG. 15C shows the filtered output for the median, or p(3/5); and FIG.15D shows the filtered output for p(4/5). The criteria p(2/5) fullyeliminated the pacing artifact (FIG. 15B), whereas the criteria p(3/5)and p(4/5) did not (FIGS. 15C and 15D, respectively). Thus, the optimalelimination of certain pacing artifacts requires nonlinear, non-medianfiltering, where the position z comprises a positive integer;

1≦z≦WL; and: ##EQU10##

FIG. 16A shows a simulated pacing artifact where AL is 5 and the widthof the highest peak is 2. FIG. 16B shows the filtered output for p(2/5);

FIG. 16C shows the filtered output for p(3/5), i.e. the median; and FIG.16D shows the filtered output for p(4/5). The criteria p(3/5) fullyeliminated the pacing artifact (FIG. 16C), whereas the criteria p(2/5)and p(4/5) did not (FIGS. 16B and 16D, respectively).

FIG. 17A shows a simulated pacing artifact where AL is 5 and the widthof the highest peak is 1. FIG. 17B shows the filtered output for p(2/5);FIG. 17C shows the filtered output for p(3/5), i.e. the median; and FIG.17D shows the filtered output for p(4/5). The criteria p(4/5) fullyeliminated the pacing artifact (FIG. 17D), whereas the criteria p(2/5)and p(3/5) did not (FIGS. 17B and 17C, respectively).

FIG. 18A shows a paced electrogram consisting of 500 samples taken inincrements of 0.5 seconds. The designation PA in FIG. 18A marks thelocation of the pacing artifact, which is 5 sample periods in length(i.e., AL=5).

FIG. 18C shows a plot of the filter output generated by filtering theelectrogram of FIG. 18A using a sample window size WL=7 (that is, lessthan twice the artifact sample size) and specifying the median p(4/7) asthe sort position. FIG. 18C shows a reduction in the size but not anelimination of the pacing artifact PA by median filtering.

FIG. 18B shows a plot of the filter output generated by filtering theelectrogram of FIG. 18A using a sample window size WL=11 (that is,WL=2AL+1), while still specifying the median p(6/11) as the sortposition. FIG. 18B shows an elimination of the pacing artifact by medianfiltering.

Except for the median filter p(3/5), the implementation of this type ofnonlinear filter will distort both the positive and negative phases ofthe useful signal (see FIGS. 15B/D, 16B/D, and 17B/D.)

B. Adaptive Filtering Alternatively, the filter 56 can implement theadaptive filtering algorithm shown in FIG. 19 to remove the pacingartifact.

The filter 56 generates an internal variable TPACE(t) expressing atemplate of the pacing artifact itself. The function TPACE(t) preferablybegins with a preestablished template typical for a pacing artifact.Alternatively, the algorithm can create an initial template by manuallyselecting a window about the artifact and creating a template by, forexample, conventional signal averaging techniques. This template couldbe adaptively updated using appropriate signal averaging techniques.

FIGS. 24 to 28 exemplify a preferred way of generating a template of thepacing artifact. FIG. 24 shows a portion of a recording of a pacedelectrogram extending over about two beats and a half. FIG. 24 showsthree pacing pulses (PA-1; PA-2; PA-3), which are the artifacts that areto be ultimately removed. The physician preferably selects windows abouteach pacing pulse PA-1 to 3 to create an averaged template.Alternatively, the physician can select one of the pacing pulse, forexample PA-1, to generate the template.

FIGS. 25A to C represent the signals PS-1; PS-2; and PS-3 contained bythe three windows manually selected about the pacing pulses,respectively PA-1; PA-2; and PA-3. The physician manually aligns thethree signals PS-1; PS-2; and PS-3 and truncates them at the samelength, as FIGS. 26A to C show. In FIGS. 26A to C, the three signalsPS-1; PS-2; and

PS-3 have been aligned about their largest positive peak, although otheralignment techniques could be used.

FIG. 27 shows the template TPACE(t) of the pacing artifact generated byaveraging the three signals PS-1; PS-2; and PS-3 after alignment andtruncation (i.e., the signals shown in FIGS. 26A to C are averaged). AsFIGS. 28A and B show, the template TPACE(t) (FIG. 28B) is aligned withthe first pacing pulse in the electrogram (FIG. 28A) prior to executingthe adaptive algorithm for artifact removal.

It is not necessary to generate a new pacing artifact template TPACE(t)for the electrogram sensed by each electrode. The same initial templateTPACE(t) from only one of the electrodes can be used for everyelectrogram. Alternatively, pacing signals from different electrodes canbe aligned for averaging to create the template TPACE(t), which is thenused for all electrograms.

The template TPACE(t) can also be generated by approximating the pacingpulse using suitable mathematical techniques, for example, splineinterpolation. A universal template TPACE(t) can also be generated fromrecordings taken from different patients at different times withdifferent equipment, although such different records may require properadjustment before generating the universal template TPACE(t).

The filter 56 expresses the input signal with respect to time IN(t) interm of the function expressed as:

IN(t)=EG(t)+PACE(t)

where:

EG(t) is the actual electrogram, and

PACE(t) is the pacing artifact.

The template TPACE(t) of the filter 56 reduces IN(t), so the outputsignal EG (t) is expressed as IN(t)-TPACE(t). The filter 56 changesTPACE(t) over time based upon the energy of the output EG (t) so as tominimize the energy of (PACE(t)-TPACE(t)) over time, and therefore, theenergy of EG (t).

Expressed differently, the filter 56 seeks to minimize the functionEG(t)+PACE(t)-TPACE(t) over time. Ideally, the energy of EG(t) isminimized over time when TPACE(t) equals PACE(t), therefore being equalto the energy of EG(t).

The filter algorithm changes TPACE(t) over time applying known iterativetechniques. For example, when applying the Least-Mean-Squares (LMS)technique, the template for TPACE(t) is used as a reference input forthe LMS algorithm. The weight vector is initialized at K 0 0 . . . 0!.The variable K is chosen equal to the ratio between the peak of PACE(t)and the peak of the template TPACE(t). When PACE(t)=TPACE(t), k is equalto one. Further details of LMS are found in "Adaptive Filter Theory" byS. Haykin (Prentice Hall, 1991)

Other conventional iterative techniques like Recursive-Least-Squares orSteepest-Descent can also be used to achieve the same result.

EXAMPLE (Adaptive Filtering)

FIG. 20A shows a representative paced electrogram. The designation PA inFIG. 20A marks the location of the pacing artifact. FIG. 20B shows thepaced electrogram after filtering using the LMS technique abovedescribed. FIG. 20B shows the effectiveness of the adaptive filter toremove the pacing artifact, without otherwise altering the morphology ofthe paced electrogram.

Either of the above described techniques for removing the pacingartifact have application outside the conditioning of the electrogramfor morphology matching described herein. Either technique hasapplication whenever it is desired to remove an artifact signal from auseful signal or to otherwise eliminate virtually any signal of a knownshape.

As a general proposition, nonlinear filtering or adaptive filtering, asabove described, can be used whenever it is desired to remove cardiacrelated or other periodic artifacts, for example, in respiratorysignals, or EEG's, or from neurological signals. Nonlinear filtering oradaptive filtering, as above described, can also be used to eliminateperiodic artifacts that are not cardiac related, for example, 50 to 60Hz noise from sensed signals due to poor power source isolation.

In the presence of a pacing artifact, nonlinear filtering or adaptivefiltering, as above described, can also be used to remove the pacingartifact before measuring the level of fractionation in an electrogram.Since a pacing artifact looks much like an electrogram, it is desirableto remove it before analyzing for actual fractionation.

As another example, nonlinear filtering or adaptive filtering, as abovedescribed, can be used to remove a pacing artifact when it is desired toconduct a frequency domain analysis of the cardiac signal, to determinethe regularity of the heart beat.

Any portion of the electrogram can be isolated for elimination using thefiltering techniques described above, not merely the pacing artifact.The nonlinear and adaptive filtering techniques can be used inapplications where low pass filtering cannot be used. For example, whilebody surface mapping can use low pass filtering of electrograms,endocardial mapping cannot, due to the use of higher frequencies than inelectrocardiograms. For example, a common electrocardiogram frequencyspectrum is 0.05 to 100 Hz, whereas a common bipolar electrogramspectrum is 1 to 300 Hz.

Nonlinear filtering or adaptive filtered, as above described, can beused for processing or analyzing virtually any signal derived from abiological event. In addition to processing or analyzing signals derivedfrom cardiac-related events, nonlinear filter or adaptive filtering canbe used to process or analyze electroencephalograms, respiratorysignals, electrogastrograms, and electromyograms.

Various features of the invention are set forth in the following claims.

We claim:
 1. An element for generating a composite signal derived frombiopotentials sensed in myocardial tissue comprisinga plurality ofsensors, first means for inputting a first set of signals comprising aplurality of biopotentials sensed in myocardial tissue using a firstgroup of the sensors during a first time interval, second means forinputting a second set of signals comprising a plurality of bipotentialssensed in myocardial tissue during a second time interval sequentiallyafter the first time interval using a second group of the sensors havingat least one common sensor that is part of the first group and othersensors that are not part of the first group, at least one of thebiopotentials in the first set of signals being sensed in the first timeinterval and not in the second time interval, and at least one of thebiopotenial in the second set of signals being sensed in the second timeinterval and not in the first time interval, and third means for timealigning the first and second sets of signals using biopotentials sensedin myocardial tissue by the at least one common sensor, therebygenerating the composite signal arranged for analysis as if allbiopotentials were sensed during a common time interval, whereby-thecomposite signal provides a diagnostic indicator.
 2. An elementaccording to claim 1wherein the first and second sets of signalscomprise electrograms.
 3. An element according to claim 1wherein thefirst and second sets of signals comprise electrocardiograms.
 4. Anelement according to claim 1wherein the third means time aligns byshifting the first and second sets of signals without computing a timedifference between them.
 5. An element according to claim 4wherein thethird means shifts the first and second sets of signals based uponlocations of maximal slopes of the signals coming from the commonsensor.
 6. An element according to claim 1wherein the third means timealigns by shifting the first and second sets of signals by computing atime difference between the first and second sets of signals for thepurpose of time-registering them.
 7. An element according to claim6wherein the third means computes the time difference based upon timedifferences of peaks of the signals coming from the common sensor.
 8. Asystem for generating a composite signal derived from biopotentialssensed in myocardial tissue comprisingmultiple sensors for sensingbiopotentials in myocardial tissue comprising a first sensor group and asecond sensor group having at least one common sensor that is part ofthe first group and other sensors that are not part of the first group,and a processing element coupled to the multiple sensors and operativefor creating the composite signal by steps comprising(i) generating afirst set of signals by conditioning the first sensor group to sense inmyocardial tissue a plurality of biopotentials during a first timeinterval, (ii) generating a second set of signals by conditioning thesecond sensor group to sense in myocardial tissue a plurality ofbiopotentials during a second time interval, the second time intervalbeing sequentially after the first time interval, at least one of thebiopotentials in the first set of signals being sensed in the first timeinterval and not in the second time interval, and at least one of thebiopotentials in the second set of signals being sensed in the secondtime interval and not in the first time interval, (iii) time aligningthe first and second sets of signals using the biopotentials sensed inmyocardial tissue by the at least one common sensor, thereby generatinga composite signal arranged for analysis as if all biopotentials weresensed during a common time interval, whereby the composite signalprovides a diagnostic indicator.
 9. A system according to claim 8andfurther including means for analyzing the composite signal.
 10. A systemaccording to claim 8wherein the first and second sets of signalscomprise electrograms.
 11. A system according to claim 8wherein thefirst and second sets of signals comprise electrocardiograms.
 12. Asystem according to claim 8wherein the processing element time aligns byshifting the first and second sets of signals without computing a timedifference between them.
 13. A system according to claim 12wherein theprocessing element shifts the first and second sets of signals basedupon locations of maximal slopes of the signals coming from the commonsensor.
 14. A system according to claim 8wherein the processing elementtime aligns by shifting the first and second sets of signals bycomputing a time difference between the first and second sets of signalsfor the purpose of time-registering them.
 15. A system according toclaim 14wherein the processing element computes the time differencebased upon time differences of peaks of the signals coming from thecommon sensor.
 16. A system for analyzing biopotential morphologies inmyocardial tissue comprisingmultiple electrodes for sensingbiopotentials in a myocardial tissue region comprising a first electrodegroup and a second electrode group having at least one common electrodethat is part of the first group and other electrodes that are not partof the first group, a processing element coupled to the multipleelectrodes and operative for creating a composite sample ofbiopotentials by steps comprising(i) generating a first set ofsignals-by conditioning the first electrode group to sense a pluralityof biopotentials occurring in the myocardial tissue region during abiopotential generating event during a first time interval, (ii)generating a second set of signals by conditioning the second electrodegroup to sense a plurality of biopotentials occurring in the myocardialtissue region during a second time interval of the biopotentialgenerating event, the second time interval being sequentially after thefirst time interval, at least one of the biopotentials in the first setof signals being sensed in the first time interval and not in the secondtime interval, and at least one of the biopotentials in the second setof signals being sensed in the second time interval and now in the firsttime interval, (iii) time aligning the first and second sets of signalsusing biopotentials sensed by the at least one common electrode, therebycreating the composite biopotential sample arranged for analysis as ifall biopotentials were sensed during a common time interval, whereby thecomposite signal provides a diagnostic indicator.
 17. A system accordingto claim 16and further including means for analyzing the compositebiopotential sample.
 18. A system according to claim 16wherein theprocessing element time aligns by shifting the first and second sets ofsignals without computing a time difference between them.
 19. A systemaccording to claim 18wherein the processing element shifts the first andsecond sets of signals based upon the locations of maximal slopes of thesignals coming from the common sensor.
 20. A system according to claim16wherein the processing element time aligns by shifting the first andsecond sets of signals by computing a time difference between the firstand second sets of signals for the purpose of time-registering them. 21.A system according to claim 20wherein the processing element computesthe time difference based upon time differences of peaks of the signalscoming from the common sensor.
 22. An apparatus for processingbiopotentials sensed first, second, and third signal sensors inmyocardial tissue, the apparatus comprisingfirst and second signalprocessing channels, and a processing element coupled to the processingchannels comprisingfirst means for coupling the first and second signalsensors to the first and second processing channels during a first timeinterval to record a first set of signals comprising a plurality ofbiopotentials sensed in myocardial tissue, second means for coupling thefirst and third signal sensors to the first and second processingchannels during a second time interval different than the first timeinterval to record a second set of signals comprising a plurality ofbiopotentials sensed in myocardial tissue, at least one of thebiopotentials in the first set of signals being sensed in the first timeinterval and not in the second, time interval, and at least one of thebiopotentials in the second set of signals being sensed in the-secondtime interval and not in the first time interval, third means for timealigning the first and second sets of signals by using biopotentialssensed by the first signal sensor to create a composite set of signalscomprising the biopotentials sensed by the first, second, and thirdsensors arranged for analysis as if all biopotential were recordedduring a common time interval, whereby the composite set provides adiagnostic indicator.
 23. An apparatus according to claim 22wherein thebiopotentials comprise electrograms.
 24. An apparatus according to claim22wherein the biopotentials comprise electrocardiograms.
 25. Anapparatus according to claim 22wherein the third means time aligns byshifting the first and second sets of signals without computing a timedifference between them.
 26. An apparatus according to claim 25whereinthe third means shifts the first and second sets of signals based uponlocations of maximal slopes of the signals coming from the first signalsensor.
 27. An apparatus according to claim 22wherein the third meanstime aligns by shifting the first and second sets of signals bycomputing a time difference between the first and second sets of signalsfor the purpose of time-registering them.
 28. An apparatus according toclaim 27wherein the third means computes the time difference based upontime differences of peaks of the signals coming from the first signalsensor.
 29. A method for generating a composite signal derived frombiopotentials sensed in myocardial tissue comprising the stepsofinputting a first set of signals comprising a plurality ofbiopotentials sensed in myocardial tissue by a first group of sensorsduring a first time interval, inputting a second set of signalscomprising a plurality of biopotentials sensed in myocardial tissueduring a second time interval sequentially after the first time intervalusing a second group of sensors having at least one common sensor thatis part of the first group and other sensors that are not part of thefirst group, at least one of the biopotentials in the first set ofsignals being sensed in the first time interval and not in the secondtime interval, and at least one of the biopotentials in the second setof signals being sensed in the second time interval and not in the firsttime interval, and time aligning the first and second sets of signalsusing biorotentials sensed by the at least one common sensor, therebygenerating the composite signal arranged for analysis as if allbiopotentials were recorded during a common time interval whereby thecomposite signal provides a diagnostic indicator.
 30. A method accordingto claim 29wherein the first and second sets of signals compriseelectrograms.
 31. A method according to claim 29wherein the first andsecond sets of signals comprise electrocardiograms.
 32. A methodaccording to claim 29wherein the time aligning step shifts the first andsecond sets of signals without computing a time difference between them.33. A method according to claim 32wherein the time aligning step shiftsthe first and second sets of signals based upon locations of maximalslopes of the signals coming from the common sensor.
 34. A methodaccording to claim 29wherein the time aligning step shifts the first andsecond sets of signals by computing a time difference between the firstand second sets of signals for the purpose of time-registering them. 35.A method according to claim 34wherein the time aligning step computesthe time difference based upon time differences of peaks of the signalscoming from the common sensor.
 36. A method using first and secondprocessing channels for processing biopotential signals sensed inmyocardial tissue by first, second, and third signal sensors, the methodcomprising the steps ofcoupling the first and second signal sensors tothe first and second processing channels during a first time interval torecord a first set of biopotential signals, coupling the first and thirdsignal sensors to the first a second processing channels during a secondtime interval different than the first time interval to record a secondset of biopotential signals, at least one of the biopotential signals inthe first set being sensed in the first time interval and not in thesecond time interval, and at least one of the biopotential signals inthe second set being sensed in the second time interval and not in thefirst time interval, and time aligning the first and second sets ofbiopotential signals based upon the biopotential signals sensed by thefirst signal sensor to create a composite set of biopotential signalscomprising the biopotential signals sensed by the first, second, andthird sensors arranged for analysis as if all biopotential signals wererecorded during a common time interval, whereby the composite set ofbiopotential signals provides a diagnostic indicator.
 37. A methodaccording to claim 36wherein the biopotentials comprise electrograms.38. A method according to claim 36wherein the biopotentials compriseelectrocardiograms.
 39. A method according to claim 36wherein the timealignment step shifts the first and second sets of biopotential signalswithout computing a time difference between them.
 40. A method accordingto claim 39wherein the time alignment step shifts the first and secondsets of biopotential signals based upon locations of maximal slopes ofthe biopotential signals coming from the first signal sensor.
 41. Anapparatus according to claim 36wherein the time alignment step shiftsthe first and second sets of biopotential signals by computing a timedifference between the first and second sets of biopotential signals forthe purpose of time-registering them.
 42. An apparatus according toclaim 41wherein the time alignment step computes the time differencebased upon time differences of peaks of the biopotential signals comingfrom the first signal sensor.